| 基于补偿模糊神经网络的自主导向车路径规划 |
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| 引用本文： | 朱云国,周松林.基于补偿模糊神经网络的自主导向车路径规划[J].冶金设备,2009(3):10-12,35. |
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| 作者姓名： | 朱云国 周松林 |
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| 作者单位： | 铜陵学院电气工程系,安徽铜陵,244000 |
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| 基金项目： | 安徽省高校省级自然科学基金资助项目 |
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| 摘 要： | 针对常规模糊神经网络的不足，提出了补偿模糊神经网络算法的自主导向车路径规划方法。该网络对介于最坏和最好输入的情况制定一个相对折中的方案。最后给出了有障碍物的环境中路径规划的仿真结果，结果表明此方法是可行的，并能有效地提高算法的收敛速度。
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| 关 键 词： | 自主导向车 路径规划 补偿模糊神经网络 |
Path Planning for Automated Guided Vehicle Based on Compensatory Fuzzy Neural Network |
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| Zhu Yunguo,Zhou Songlin.Path Planning for Automated Guided Vehicle Based on Compensatory Fuzzy Neural Network[J].Metallurgical Equipment,2009(3):10-12,35. |
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| Authors: | Zhu Yunguo Zhou Songlin |
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| Affiliation: | Zhu Yunguo Zhou Songlin ( Tongling college, Anhui, Tongling 244000) |
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| Abstract: | In order to overcome the drawbacks of conventional fuzzy neural networks, a compensatory fuzzy neural network is proposed to plan path for Automated Guided Vehicle. The network makes a middle decision between the worst and the best condition. At last, path planning simulation is carried out in the environment with obsta- cles. The simulation result indicates that the method is feasible and it validly improves the convergence velocity. |
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| Keywords: | Automated guided vehicle Path planning Compensatory fuzzy neural network |
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